Core Coursework: Database Systems (SQL), Applied Linear Models, Data Structures & Algorithms, Object-Oriented Programming (Python/Java), and Statistical Inference.

• Analyzed metric performance via Meta Business Suite to scale organic account reach up to 70,000 followers.
• Formulated content strategy based on audience retention patterns, averaging 10,000 engagements per post.

Managed OBS Studio streaming setups, network routing, and hardware troubleshooting ensuring continuous zero downtime live broadcasts.

Developed a production-ready Point of Sale (POS) system for barbershop operations. Features service catalog management, product retail tracking, clean transaction processing, real-time analytics dashboard, and automated database cleanup procedures for client handover.

Engineered a role-based POS web system (Owner vs Cashier) designed to optimize inventory tracking for complex vape variants (nicotine levels, ohm resistance) and real-time Net Profit/COGS calculation. Features fast-tap cashier interface, multi-payment tracking (Cash, QRIS, BCA Transfer), and automated daily sales analytics.

Extracted raw binary memory dumps from vehicle ECU flash memory. Developed automated Python scripts using byte-pattern matching to convert raw hexadecimal data into structured numerical matrices for interactive 3D surface visualizations.

Constructed a Multiple Logistic Regression econometric model using Pandas and Statsmodels to predict household vehicle asset ownership. Processed thousands of micro-sample rows from BPS national survey data, performing data cleaning, outlier removal, and multicollinearity diagnostics.

Designed interactive business intelligence dashboards in Tableau Desktop to track operational KPIs. Integrated complex Excel matrix functions (XLOOKUP, INDEX/MATCH, Pivot Tables) to streamline periodic reporting workflows.

Engineered a multi-threaded Python data pipeline utilizing concurrent.futures to ingest real-time fundamental and 1-year historical price data from Yahoo Finance API for IHSG stocks. Programmed an automated stock screener combining financial ratios (PER, PBV, ROE) with technical indicators (MA20/50, RSI-14) to spot undervalued, high-profitability stocks in active uptrends, accompanied by dynamic dual-panel Seaborn visualizations and CSV exports.

Developed a real-time computer vision system using Python and OpenCV. Engineered multi-functional modules capable of real-time object detection, face recognition, and interactive hand-gesture tracking for dynamic UI control and visual data processing.